Current status and progress of PD-L1 detection: guiding immunotherapy for non-small cell lung cancer

Chang Qi1,2, Yalun Li1,2, Hao Zeng1,2

  • 1Department of Pulmonary and Critical Care Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, Institute of Respiratory Health and Multimorbidity, Institute of Respiratory Health, Frontiers Science Center for Disease-related Molecular Network, Precision Medicine Center/Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Insights

This review explores advanced methods for detecting Programmed Death-Ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC). It aims to improve patient selection for immunotherapy by analyzing diverse detection techniques and biomarkers.

Area of Science:

  • Oncology
  • Immunology
  • Medical Diagnostics

Background:

  • Non-small cell lung cancer (NSCLC) is a leading cause of cancer mortality globally.
  • Immune checkpoint inhibitors plus chemotherapy are standard first-line treatment for advanced NSCLC without driver mutations.
  • Programmed Death-Ligand 1 (PD-L1) is the sole approved biomarker for immunotherapy efficacy.

Purpose of the Study:

  • To review and analyze diverse methods for detecting PD-L1 expression in NSCLC.
  • To discuss challenges, influencing factors, and the value of combined biomarkers in PD-L1 detection.
  • To support clinical screening for immunotherapy-responsive patients and personalized treatment strategies.

Main Methods:

  • Review of current literature on PD-L1 detection methodologies.
  • Analysis of immunohistochemistry, liquid biopsy, genetic testing, and radionuclide imaging.
  • Exploration of machine learning models for PD-L1 prediction.

Main Results:

  • PD-L1 detection methods are rapidly evolving, offering diverse approaches.
  • Various factors influence PD-L1 detection accuracy and reliability.
  • Combined biomarkers show potential for enhanced predictive value.

Conclusions:

  • Accurate PD-L1 detection is crucial for optimizing immunotherapy in NSCLC.
  • Emerging technologies offer promising avenues for improved diagnostic accuracy.
  • Personalized treatment decisions can be enhanced through comprehensive biomarker analysis.